Are multiseasonal forecasts of atmospheric rivers possible?

Kai-Chih Tseng

NOAA/GFDL and Princeton University

Tuesday, Nov 23, 2021, 2:00 pm

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Abstract

Atmospheric rivers (ARs) exert significant socioeconomic impacts in western North America, where 30% of the annual precipitation is determined by ARs that occur in less than 15% of winter time. ARs are thus beneficial to water supply but can produce extreme precipitation hazards when making landfall. While most prevailing research has focused on the subseasonal (< 5 weeks) prediction of ARs, only limited efforts have been made for AR forecasts on multiseasonal timescales (≥ 3 months) that are crucial for water resource management and disaster preparedness. Through the analysis of reanalysis data and retrospective predictions from a new seasonal-to-decadal forecast system, this research shows the existing potential of multiseasonal AR frequency forecasts with predictive skills 9 months in advance. Additional analysis explores the dominant predictability sources and challenges for multiseasonal AR prediction.

Speaker Bio: Dr. Tseng is a postdoctoal researcher at NOAA/GFDL and Princeton University working with Dr. Nat Johnson. Currently, his research interests are the prediction and predictability of extreme weather from a dynamical system perspective. He is also interested in numerical modeling (e.g., GPU dynamical core, a.k.a. making climate models simpler and go faster), artificial intelligence (e.g., Deep Learning) and statistical methods. Dr. Tseng got his PhD in June 2019 from Colorado State University, where his advisors were Dr. Elizabeth Barnes and Dr. Eric Maloney. In summer 2022, he will begin an Assistant Professorship in the Department of Atmospheric Science, National Taiwan University. Dr. Tseng's website is https://kuiper2000.github.io/.